Insight • Marc Schmitt

NIS2 & AI - A C-Level Readiness Article on Consequences, Risks, and Required Actions

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Free expert overview by Marc Schmitt

Understanding NIS2 and AI: What Leaders Need to Know

The NIS2 Directive is a new cybersecurity regulation that impacts organizations providing essential services, especially those using artificial intelligence (AI) in their operations. While NIS2 does not regulate AI directly, it treats AI systems as part of the broader IT infrastructure, meaning AI must meet the same cybersecurity standards as other critical technologies.

Why AI Matters Under NIS2

AI systems embedded in important business processes or handling sensitive data are subject to strict cybersecurity rules. This includes managing risks, securing supply chains, reporting incidents quickly, and ensuring clear leadership accountability. The more AI is integrated into your operations, the more rigorous your compliance requirements become.

Key AI Risks to Watch

Data Leakage: Sensitive information can be exposed if AI tools are misconfigured or accessed improperly.
Data Poisoning: Attackers may corrupt AI training data, causing harmful or incorrect AI behavior.
API Misuse: Stolen or poorly managed API keys can allow unauthorized access to AI systems.
System Outages: Targeted attacks can disrupt AI services, impacting critical operations.
Supply Chain Risks: Vulnerabilities in third-party AI providers can expose your organization to breaches.

Leadership Responsibilities

Executives must ensure AI is included in risk assessments and governance frameworks. This means maintaining transparency about AI assets, enforcing strict access controls, reviewing AI vendors carefully, monitoring AI system activity continuously, and preparing for incidents with clear response plans.

Practical Steps for Compliance

Start by recognizing AI as a core IT risk and assessing AI-specific threats. Establish clear governance roles, implement minimum security controls, manage supply chain risks proactively, and prepare for incident reporting within 24 hours. Finally, integrate AI security into your overall risk management and foster a culture of AI security awareness across your organization.

Conclusion

NIS2 reframes AI from a mere innovation tool to a systemic risk factor requiring board-level oversight. By embedding AI within cybersecurity governance, organizations can safely leverage AI’s benefits while meeting regulatory requirements and protecting their reputation.

Key steps

Recognize AI as a Core IT Risk Under NIS2
Understand that AI systems integrated into critical business processes and data environments are subject to the same cybersecurity obligations as other IT assets under the NIS2 Directive. Executive leadership must acknowledge AI’s role within the IT risk landscape and ensure it is included in risk assessments, governance frameworks, and compliance efforts.
Identify and Assess AI-Specific Cybersecurity Risks
Evaluate concrete AI-related risks such as data leakage, data poisoning, API misuse, system outages, and supply chain vulnerabilities. Recognize how these risks can impact operational continuity, reputation, and regulatory compliance, and prioritize them within your organization’s cybersecurity risk management.
Establish Clear Governance and Accountability for AI Security
Assign explicit responsibilities for AI security at the executive and board levels. Ensure AI is integrated into enterprise risk management, vendor evaluations, and incident response plans. Leadership must demonstrate oversight and maintain documented evidence of AI security governance to meet NIS2 obligations.
Implement Operational Minimum Controls for AI Systems
Adopt a baseline framework including transparency (inventory and data flows), access control (role-based permissions and credential management), supply chain review (vendor certifications and contracts), continuous monitoring (logging and anomaly detection), and incident preparedness (fallbacks and escalation procedures) to manage AI cybersecurity risks effectively.
Manage AI Supply Chain Risks Proactively
Incorporate AI vendors and providers into your supply chain risk management processes. Conduct thorough security assessments, demand transparency about subcontractors, and include contractual clauses requiring timely incident reporting to mitigate third-party risks under NIS2.
Prepare for Incident Reporting and Response
Develop and test incident response plans that specifically address AI-related cybersecurity events. Ensure readiness to report incidents within the 24-hour window mandated by NIS2, including clear escalation paths and communication strategies to minimize operational and reputational damage.

FAQ

What is the significance of the NIS2 Directive for organizations using AI?

NIS2 integrates AI systems into the regulated IT infrastructure for organizations providing essential services. AI is subject to the same cybersecurity obligations as other IT assets, requiring executive leadership to include AI in risk assessments, governance, supply chain oversight, and incident reporting within 24 hours. This ensures AI is managed as a systemic risk factor, not just an innovation tool.

How does NIS2 treat AI systems within the IT risk landscape?

NIS2 treats AI as part of the overall IT infrastructure, subjecting AI applications that process sensitive data or influence critical decisions to the same cybersecurity obligations as traditional IT systems. Organizations must explicitly include AI in risk assessments, governance, and controls, with leadership accountability for oversight and compliance.

What are the main cybersecurity risks introduced by AI under NIS2?

Key AI cybersecurity risks under NIS2 include data leakage, data poisoning, API misuse, system outages, and supply chain vulnerabilities. These risks can cause operational disruption, reputational harm, and regulatory penalties, necessitating proactive governance, monitoring, and incident response.

What governance and accountability responsibilities do executive leaders have regarding AI security under NIS2?

Executive leaders are accountable for integrating AI into risk assessments and governance, assigning clear security roles, ensuring vendor evaluations, and establishing AI-specific incident response processes. They must maintain auditable oversight to demonstrate compliance and reduce liability.

What operational minimum controls should organizations implement for AI systems to comply with NIS2?

Organizations should implement controls including AI system inventories and data flow transparency, role-based access control, rigorous supply chain reviews, continuous monitoring with anomaly detection, and incident preparedness with fallback and escalation plans to meet NIS2 requirements.

Marc Schmitt